NCAR's Data Assimilation Research Section

The NCAR Data Assimilation Initiative was founded to create and to then
lead a research community for data assimilation where individuals benefit
from sharing ideas, methodologies, and software tools as well as access to
a data assimilation testbed. NCAR has a large number of researchers for
whom data assimilation is an essential part of their ongoing or planned
research. New developments in theoretical data assimilation and in software
engineering are making collaborations between data assimilation experts,
modelers, observational specialists and statisticians easier and more
productive than was possible in the past.
The maturation of the Initiative resulted in the Data Assimilation
Research Section (DAReS): a component of the Institute for
Mathematics Applied to Geosciences.
The primary goal of DAReS is to continue to advance the theory and
practice of ensemble data assimilation.
Also, DAReS accelerates the progress of many other NCAR
projects by providing a centralized data assimilation expertise which can
be coordinated with existing observational and modeling expertise.

Ensemble Filters for
Geophysical Data Assimilation

Click on Image to Download DART

The Data Assimilation Research Testbed Facility : DART

The Data Assimilation Research Testbed (DART), is a
software environment for making it easy to match a variety of data
assimiliation methods to different numerical models and different kinds of
observations.
DART has been through the crucible of many compilers and platforms.
It is ready for friendly use and has been used in several field programs
requiring real-time forecasting. The DART source code is distributed through
our anonymous subversion server (meaning you don't need an account on our
machines) after you fill out a trivial form asking for your name, email
address, and institution. We need to gather summary statistics to
maintain an email list should there be an important update and to
help us quantify our impact on the community.
This is an ultra-low-traffic email list.
We have never sent an email to the entire list!
Please be assured we will keep your email address confidential.

The "Lanai" version of DART was released in December 2013 and contains
many stable bugfixes and improvements over the Kodiak version.
The DART source code and documentation can be downloaded at
www.image.ucar.edu/DAReS/DART/DART_download.
The most current version of the documentation is (always) distributed with the code,
but if you want to take a look before downloading, visit the
Lanai release document.

The most current version of the
documentation is distributed with the code, but if you want an idea of what
it takes to build DART and run experiments before downloading, look at the
Getting Started page.

Schematic of Ensemble Data Assimilation - from the DAReS Perspective

This is the DART view of ensemble data assimilation for models that
run as separate executables. Starting at the top and working clockwise:
Everything is driven by a Fortran namelist and the
presence or absence of observations. A Fortran executable named
'filter' reads a namelist, an initial state for the ensemble, and a
file containing observations and goes to work. Given the observations
and an initial state, 'filter' assimilates the observations and then
determines how far to advance the model (using information from the
namelist and the observation file). 'filter' forks a
shell script to the system and it is this shell script that
is responsible for three things: 1) for converting the DART state
vectors and 'advance_to_time' to the format required by the
underlying model, 2) advancing the model, and 3) converting the
model output into a form suitable for 'filter'. [The script is
responsible for the lower portion of the diagram.] The model advances
each ensemble member (either in turn or all-at-once) and the model
output is converted to the input format expected by 'filter'. The
shell script finishes and signals 'filter' to continue. We are now
back at the beginning and the cycle continues as long as there are
observations to assimilate or until the control information in the
Fortran namelist is met. When that happens, a set of restart files
is written (suitable to continue an experiment with more observations)
and diagnostic files are written. These diagnostic files allow for
the exploration of the assimilation before and after each assimilation
step and for exploration of the assimilation in 'observation space';
each real observation is paired with the estimates of the observation
from all of the ensemble members (if desired). Minimally, the ensemble
mean estimate of the observation and the ensemble spread of the estimates
is recorded.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.
Any opinions, findings and conclusions or recommendations expressed in this publication are those
of the author(s) and do not necessarily reflect the views of the National Science Foundation.